Modelling Stock Market Volatility: Evidence from India

This study empirically investigates the volatility pattern of Indian stock market based on time series data which consists of daily closing prices of S&P CNX Nifty Index for ten years period from 1st January 2003 to 31st December 2012. The analysis has been done using both symmetric and asymmetr...

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Main Authors: Karunanithy Banumathy, Ramachandran Azhagaiah
Format: Article
Language:English
Published: University of Primorska 2015-03-01
Series:Managing Global Transitions
Subjects:
Online Access:http://www.fm-kp.si/zalozba/ISSN/1581-6311/13_027-041.pdf
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spelling doaj-c9d8bbfbffb5406880d6ee1c4082e16b2020-11-24T22:51:45ZengUniversity of PrimorskaManaging Global Transitions1581-63111854-69352015-03-011312741Modelling Stock Market Volatility: Evidence from IndiaKarunanithy Banumathy0Ramachandran Azhagaiah1Pondicherry Central University, IndiaPondicherry Central University, IndiaThis study empirically investigates the volatility pattern of Indian stock market based on time series data which consists of daily closing prices of S&P CNX Nifty Index for ten years period from 1st January 2003 to 31st December 2012. The analysis has been done using both symmetric and asymmetric models of Generalized Autoregressive Conditional Heteroscedastic (GARCH). As per Akaike Information Criterion (AIC) and Schwarz Information Criterion (SIC), the study proves that GARCH (1,1) and TGARCH (1,1) estimations are found to be most appropriate model to capture the symmetric and asymmetric volatility respectively. The study also provides evidence for the existence of a positive and insignificant risk premium as per GARCH-M (1,1) model. The asymmetric effect (leverage) captured by the parameter of EGARCH (1,1) and TGARCH (1,1) models show that negative shocks have significant effect on conditional variance (volatility).http://www.fm-kp.si/zalozba/ISSN/1581-6311/13_027-041.pdfasymmetric volatilityconditional volatilityGARCH models and leverage effect
collection DOAJ
language English
format Article
sources DOAJ
author Karunanithy Banumathy
Ramachandran Azhagaiah
spellingShingle Karunanithy Banumathy
Ramachandran Azhagaiah
Modelling Stock Market Volatility: Evidence from India
Managing Global Transitions
asymmetric volatility
conditional volatility
GARCH models and leverage effect
author_facet Karunanithy Banumathy
Ramachandran Azhagaiah
author_sort Karunanithy Banumathy
title Modelling Stock Market Volatility: Evidence from India
title_short Modelling Stock Market Volatility: Evidence from India
title_full Modelling Stock Market Volatility: Evidence from India
title_fullStr Modelling Stock Market Volatility: Evidence from India
title_full_unstemmed Modelling Stock Market Volatility: Evidence from India
title_sort modelling stock market volatility: evidence from india
publisher University of Primorska
series Managing Global Transitions
issn 1581-6311
1854-6935
publishDate 2015-03-01
description This study empirically investigates the volatility pattern of Indian stock market based on time series data which consists of daily closing prices of S&P CNX Nifty Index for ten years period from 1st January 2003 to 31st December 2012. The analysis has been done using both symmetric and asymmetric models of Generalized Autoregressive Conditional Heteroscedastic (GARCH). As per Akaike Information Criterion (AIC) and Schwarz Information Criterion (SIC), the study proves that GARCH (1,1) and TGARCH (1,1) estimations are found to be most appropriate model to capture the symmetric and asymmetric volatility respectively. The study also provides evidence for the existence of a positive and insignificant risk premium as per GARCH-M (1,1) model. The asymmetric effect (leverage) captured by the parameter of EGARCH (1,1) and TGARCH (1,1) models show that negative shocks have significant effect on conditional variance (volatility).
topic asymmetric volatility
conditional volatility
GARCH models and leverage effect
url http://www.fm-kp.si/zalozba/ISSN/1581-6311/13_027-041.pdf
work_keys_str_mv AT karunanithybanumathy modellingstockmarketvolatilityevidencefromindia
AT ramachandranazhagaiah modellingstockmarketvolatilityevidencefromindia
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